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A New Approach in Short-Term Prediction of the Electrical Charge with Regression Models A Case Study

A New Approach in Short-Term Prediction of the Electrical Charge with Regression Models A Case Study

Farhad Soleimanian Gharehchopoghi, Freshte Dabaghchi Mokri, Maryam Molany
Copyright: © 2013 |Volume: 4 |Issue: 3 |Pages: 13
ISSN: 1947-8283|EISSN: 1947-8291|EISBN13: 9781466633988|DOI: 10.4018/ijamc.2013070103
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MLA

Gharehchopoghi, Farhad Soleimanian, et al. "A New Approach in Short-Term Prediction of the Electrical Charge with Regression Models A Case Study." IJAMC vol.4, no.3 2013: pp.34-46. http://doi.org/10.4018/ijamc.2013070103

APA

Gharehchopoghi, F. S., Mokri, F. D., & Molany, M. (2013). A New Approach in Short-Term Prediction of the Electrical Charge with Regression Models A Case Study. International Journal of Applied Metaheuristic Computing (IJAMC), 4(3), 34-46. http://doi.org/10.4018/ijamc.2013070103

Chicago

Gharehchopoghi, Farhad Soleimanian, Freshte Dabaghchi Mokri, and Maryam Molany. "A New Approach in Short-Term Prediction of the Electrical Charge with Regression Models A Case Study," International Journal of Applied Metaheuristic Computing (IJAMC) 4, no.3: 34-46. http://doi.org/10.4018/ijamc.2013070103

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Abstract

The accuracy of forecasting of electrical load for the electricity industry has a vital significance in the renewal of economic structure as well as various equations including: purchasing and producing energy, load fluctuation, and the development of infrastructures. Its short-term forecasting has a significant role in designing and utilizing power systems and in the distribution systems and having a variety of systems used to maintain security potentials for the system. In this paper, we attempted to carry out a short-term forecasting of electrical distribution company in west Azerbaijan state in Iran's electricity in a few days on the basis of regression multi linear model. This forecasting which was done during a three-day period is and categorized weekdays into three groups including working days, weekends, and holidays was carried out in an hourly manner. This model regardless of parameters like humidity, wind velocity, daylight time, etc. by minimizing the forecasting error managed to maximize the reliability of the results as well as the safety potential of the system. In this model the only influential parameter on the forecasting was the reliance of the forecasting day on previous days. The main purpose of the present study was to maximize the accuracy and reliability of forecasting for certain days (religious holidays, national holidays …). In this paper, the authors managed to decrease the error of forecasting for particular and regular off days to a great extent.

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